Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations 2021 Multiscale analysis framework for the Iowa Water-Energy-Food nexus Weiquan Luo Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/etd Recommended Citation Luo, Weiquan, "Multiscale analysis framework for the Iowa Water-Energy-Food nexus" (2021). Graduate Theses and Dissertations. 18546. https://lib.dr.iastate.edu/etd/18546 This Thesis is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Multiscale analysis framework for the Iowa Water-Energy-Food nexus by Weiquan Luo A thesis submitted to the graduate faculty in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Major: Agricultural and Biological Engineering Program of Study Committee: Amy L. Kaleita, Co-major Professor Adina Howe, Co-major Professor Philip M. Dixon The student author, whose presentation of the scholarship herein was approved by the program of study committee, is solely responsible for the content of this thesis. The Graduate College will ensure this thesis is globally accessible and will not permit alterations after a degree is conferred. Iowa State University Ames, Iowa 2021 Copyright © Weiquan Luo, 2021. All rights reserved. ii DEDICATION This dissertation is dedicated to Chenxi Zhang, whose support and encouragement made the completion of this work possible and my parents, Yongde Luo and Huiying Chen, whose trust strengthen me to overcome all challenges along this way. iii TABLE OF CONTENTS Page LIST OF FIGURES ........................................................................................................................ v ACKNOWLEDGEMENTS ........................................................................................................... vi ABSTRACT .................................................................................................................................. vii CHAPTER 1. GENERAL INTRODUCTION ............................................................................... 1 1.1 Background ........................................................................................................................... 1 1.2 Existing Methods and Challenge .......................................................................................... 2 1.3 Objectives ............................................................................................................................. 4 1.4 References ............................................................................................................................. 4 CHAPTER 2. METHOD ................................................................................................................ 7 2.1 Data Aggregation to Multiscale ............................................................................................ 8 2.2 Probabilistic Graphical Model .............................................................................................. 9 2.3 References ........................................................................................................................... 11 CHAPTER 3. INVESTIGATE LINKAGES IN IOWA WATER-ENERGY-FOOD NEXUS USING SPARSE MARKOV RANDOM FIELD AT MULTISCALE ........................................ 12 3.1 Abstract ............................................................................................................................... 12 3.2 Introduction ......................................................................................................................... 12 3.3 Study Area .......................................................................................................................... 15 3.4 Data Collection and Scale ................................................................................................... 15 3.5 Method ................................................................................................................................ 17 3.5.1 Data Integration to Resolve Heterogeneity .................................................................. 18 3.5.2 Sparse Exponential Markov Random Fields Formulation ........................................... 19 3.6 Result and Discussion ......................................................................................................... 22 3.6.1 Feature Dimension and Sampling Density .................................................................. 22 3.6.2 Model at Multiple Scales ............................................................................................. 24 3.6.3 Network Analysis ......................................................................................................... 27 3.6.4 Water-Centric vs. Multi-Centric .................................................................................. 30 3.6.5 Limitation ..................................................................................................................... 31 3.7 Conclusion .......................................................................................................................... 33 3.8 References ........................................................................................................................... 34 Appendix: Data Description and Sources With Details Of Spatiotemporal Upscaling ............ 37 CHAPTER 4. GENERAL CONCLUSIONS ................................................................................ 38 iv APPENDIX A: NECESSARY FUNCTIONS TO RUN ANALYSIS ......................................... 40 APPENDIX B: CODE FOR CLEAN POLYGON DATA ........................................................... 56 APPENDIX C: CODE FOR WATER DATA QUERYING ........................................................ 67 APPENDIX D: CODE FOR WEATHER DATA QUERYING ................................................... 71 APPENDIX E: CODE FOR DATA INTEGRATION AND MODELING ................................. 73 v LIST OF FIGURES Page Figure 1: A county-level map of Iowa State with the boundary of nine agriculture districts ....... 17 Figure 3: Workflow of the WEF nexus modeling ........................................................................ 17 Figure 4: The comparison of integrated datasets .......................................................................... 24 Figure 5: The result of sparse Markov network at nine levels of spatiotemporal resolutions ...... 25 Figure 6: The histogram of degree distribution at nine spatiotemporal resolution. ...................... 28 Figure 7: the comparison of the networks on the assortativity coefficient ................................... 29 Figure 8: the average betweenness of variables ............................................................................ 30 vi ACKNOWLEDGEMENTS I would like to first thank my advisors, Amy L. Kaleita and Adina Howe, for the years of guidance professionally and academically throughout my master’s program. They inspired me how my wrongness become science, or I would give up from my master’s program. I would like to thank my committee members Dr. Philip M. Dixon for the time, and meaningful input. I would like to thank my graduate student colleagues, Vishal Raul, Mingjun Ma, Paul Villanueva, Qing He, and Vitor Souza-Martins who have all made a positive impact on my experience throughout graduate school. I would like to thank the Department of Agricultural and Biosystems Engineering at Iowa State University for providing the great support of this works, and for the faculty who are always encouraging and supportive. I have been provided the opportunity to be successful in part from all of the people above and many more. I am grateful for all the support, encouragement, guidance, funding, and effort that all have provided to me during this process. vii ABSTRACT This research explored Iowa’s Water-Energy-Food (WEF) resource system by modeling with Markov random field and analyzing with network analysis. With recognizing the gap between nexus modeling and communication in WEF resource management, the purpose of this research was to close the gap by proposing a framework of modeling and analyzing heterogeneous data in the WEF nexus discipline. The proposed framework aimed to discover interlinkage and characterize structural patterns between domains of Iowa’s WEF resource system. The biophysical and economic data were collected from multiple sources and processed with a standardized data aggregation pipeline. The first objective of this research was focused on the modeling method. The goal for this part of the research is to determine the technique to model Iowa’s WEF resource system. The appropriate technique helps to identify the interlinkages between components with minimal subjectivity and closes the gap of communication via intuitive visualizations. We considered the model by the data availability and the capabilities of modeling and direct visualization at different scale. As a result, we proposed the method of coupling the data aggregation pipeline with the probabilistic graphical model that uses the same scheme to model and visualize a large- scale system at different scales. The second objective of this research was focused on the characterization of Iowa’s